The engineering programme at École des Ponts ParisTech prepares each student to become a real player in sustainable development and planning in all its dimensions. Engineers graduating from École des Ponts ParisTech are recognized by companies for their strong scientific skills combined with a capacity for practical implementation of knowledge and projects.
Engineering education at École des Ponts ParisTech leads to the development of skills in four dimensions:
- Advanced scientific and technical education: understanding and implementing conceptual, mathematical or numerical modelling approaches while knowing how to critically evaluate the results of a model is one of the foundations of the engineering profession that the School's training enables students to master.
- Project-based and on-the-job training: from the very first year, numerous collective or individual projects are developed, increasingly close to real engineering projects. For students entering the first year, four internships in laboratories and companies will punctuate the curriculum.
- Managerial, human and social skills: integrated from the first year, the human and social sciences give students an understanding of the world and the ability to take into account the problems of society. A solid knowledge of the business world is developed through courses, internships and projects.
- The ability to work in a team and to work internationally: 20% of teaching time is devoted to languages. International stays and contact with many foreign students enable engineering students to learn to work in a multicultural context.
In the context of admissions of international students from partner institutions, it should be specified that:
- The engineering degree from Ecole des Ponts ParisTech is a general engineering degree with prerequisites common to all teaching departments in the School's core disciplines: Mathematics (Optimization, Probability, Analysis and Scientific Computing), Continuous and Solid Mechanics, Quantum Physics and Statistics, Programming, Human and Social Sciences.
- The vast majority of courses in engineering training are in French. A B1 level in French is therefore required to be proven by a certificate (TEF, TCF, DELF, or DALF).
- A TOEIC score of at least 785 points (or an equivalent international test, such as TOEFL, IELTS or Cambridge Proficiency, CAE or FCE) is required in order to obtain an engineering degree from Ecole des Ponts ParisTech at the end of the course. For this reason, a B1 level in English is required for admission, to be proven by a certificate (IELTS, TOEFL, TOEIC, CAMBRIDGE).
In addition, each department of engineering education has specific prerequisites:
Civil and Structural Engineering Department
Scientific analysis and calculation
Fundamental numerical methods for the engineer: finite differences for time integration of evolutionary equations, finite elements for solving variational problems.
Linear algebra, matrix calculus, tensor calculus.
Laplace transform, Fourier transform.
Partial differential equations and finite elements
- Kinematics and dynamics of non-deformable solids
- Geometric Transformation: Eulerian and Lagrangian Descriptions
- Internal stresses for 3D continuous medium: Cauchy stress tensor, Green-Lagrange strain tensor, linearization
- Thermodynamic approach to linear thermoelastic behavior, three-dimensional linear thermo elasticity problems
- Flat deformations
- Theorem of kinetic energy
- The Theorems of Minimum Potential Energy and Complementary Energy
- Principle of the finite element method in linear elasticity
- Linear elasticity finite element method
- Concepts of Limit Analysis and the Study of Linear Elastic Curvilinear Media
- Eulerian Kinematics
- Euler's equations
- Navier-Stokes equations
- Reynolds Number Irrotational plane flows of perfect incompressible fluid
- Actual and complex potential
- Conformal transformations
- Transformation and Zhukovsky profiles
- Fundamental notions (probability space, random variable, law, expectation ...)
- Usual laws with real and integer values.
- Concepts of convergence
- Strong Law of Large Numbers
- Central Limit Theorem
- Main algorithms for simulating random variables
- Monte-Carlo method